ItemPath MCP Server for OpenAI Agents SDK 10 tools — connect in under 2 minutes
The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect ItemPath through Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails. no manual schema definitions required.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
async with MCPServerStreamableHttp(
url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
) as mcp_server:
agent = Agent(
name="ItemPath Assistant",
instructions=(
"You help users interact with ItemPath. "
"You have access to 10 tools."
),
mcp_servers=[mcp_server],
)
result = await Runner.run(
agent, "List all available tools from ItemPath"
)
print(result.final_output)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About ItemPath MCP Server
Empower your AI agents to manage your warehouse and inventory with ItemPath. This MCP server allows you to list materials, retrieve order details, track inventory transactions, and view storage locations directly through the ItemPath API. Ideal for automating supply chain operations and stock monitoring.
The OpenAI Agents SDK auto-discovers all 10 tools from ItemPath through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns. chain multiple agents where one queries ItemPath, another analyzes results, and a third generates reports, all orchestrated through Vinkius.
The ItemPath MCP Server exposes 10 tools through the Vinkius. Connect it to OpenAI Agents SDK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect ItemPath to OpenAI Agents SDK via MCP
Follow these steps to integrate the ItemPath MCP Server with OpenAI Agents SDK.
Install the SDK
Run pip install openai-agents in your Python environment
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com
Run the script
Save the code above and run it: python agent.py
Explore tools
The agent will automatically discover 10 tools from ItemPath
Why Use OpenAI Agents SDK with the ItemPath MCP Server
OpenAI Agents SDK provides unique advantages when paired with ItemPath through the Model Context Protocol.
Native MCP integration via `MCPServerSse`, pass the URL and the SDK auto-discovers all tools with full type safety
Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure
Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate
First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output
ItemPath + OpenAI Agents SDK Use Cases
Practical scenarios where OpenAI Agents SDK combined with the ItemPath MCP Server delivers measurable value.
Automated workflows: build agents that query ItemPath, process the data, and trigger follow-up actions autonomously
Multi-agent orchestration: create specialist agents. one queries ItemPath, another analyzes results, a third generates reports
Data enrichment pipelines: stream data through ItemPath tools and transform it with OpenAI models in a single async loop
Customer support bots: agents query ItemPath to resolve tickets, look up records, and update statuses without human intervention
ItemPath MCP Tools for OpenAI Agents SDK (10)
These 10 tools become available when you connect ItemPath to OpenAI Agents SDK via MCP:
get_material
Returns SKU details, storage rules, and quantity-on-hand. Essential for analyzing the status of specific inventory items. Retrieves details for a specific material
get_me
Use to verify connection health and current user identity. Gets current authenticated user info
get_order
Returns the list of materials involved, target locations, and picker information. Use this for troubleshooting order fulfillment or providing status updates. Retrieves details for a specific order
list_batches
Essential for managing perishable goods or regulated materials requiring lot tracking. Lists all material batches
list_calls
Useful for debugging integrations and monitoring system interaction frequency. Lists recent API request history
list_locations
Useful for understanding warehouse layout and identifying where specific materials are stored. Lists all storage locations
list_materials
Returns material names, descriptions, and IDs. Use this to identify products for inventory auditing or order analysis. Lists all materials in ItemPath
list_orders
Includes order IDs, types, and current status. Essential for monitoring warehouse throughput and workflow. Lists all orders
list_transactions
Returns timestamps, material IDs, quantity changes, and user IDs. Essential for auditing inventory accuracy and identifying recent stock changes. Lists all inventory transactions
list_users
Useful for identifying who performed specific inventory transactions. Lists all system users
Example Prompts for ItemPath in OpenAI Agents SDK
Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with ItemPath immediately.
"List all active materials in the warehouse."
"Show me the details for order ID 'ORD-123'."
"Check recent inventory transactions."
Troubleshooting ItemPath MCP Server with OpenAI Agents SDK
Common issues when connecting ItemPath to OpenAI Agents SDK through the Vinkius, and how to resolve them.
MCPServerStreamableHttp not found
pip install --upgrade openai-agentsAgent not calling tools
ItemPath + OpenAI Agents SDK FAQ
Common questions about integrating ItemPath MCP Server with OpenAI Agents SDK.
How does the OpenAI Agents SDK connect to MCP?
MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.Can I use multiple MCP servers in one agent?
MCPServerSse instances to the agent constructor. The agent can use tools from all connected servers within a single run.Does the SDK support streaming responses?
Connect ItemPath with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect ItemPath to OpenAI Agents SDK
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.